Our products are developed for health monitoring, diagnostics, and predictive maintenance of rotating machines and are a part of the Enertics
Asset Health Monitoring and Management suite of applications.
eM PreA (Predictive Analytics)
The revolutionary eM PreA module automatically evaluates sensor data to discover anomalies before they become major problems. It features AI-based sensor data prediction analytics as well as a machine learning-based alert management system that alerts users about potentially harmful machine conditions.
Algorithms are also used by Enertics eM PreA to forecast individual fault conditions. Not only is it possible to forecast individual sensor data using advanced sensors, but it is also possible to foresee specific machine faults. Hourly, daily, weekly, and monthly timelines are used in the forecasting.
– Predictive Checks are required for almost all electrical or mechanical systems to avoid unexpected failures
– Troubleshooting issues after the failures costs a lot of money for the equipment owners and operators
– Predominantly there is no proactive information available to detect machine irregularities before they turn into major issue
– Even though a large amount of sensor data is generated by a range of industrial assets, finding Trained Resources to spot defects in advance remains a challenge
– Need for an Automated Predictive Analytic Tool is required to deliver relevant insights to the maintenance personnel
– This technique should aid in the early detection of asset issues before they develop into a crisis
– A Well-Designed Predictive System assists users in Early Predictions and Diagnosis of Potential Issues with their critical equipment
– To focus on Processess that will help establish an Effective Asset Performance Management (APM) system to reduce Asset Downtime and Production Losses.
OUR CRITICAL CONTRIBUTION
– Innovative and automatic evaluation of sensor data to detect anomalies before they turn into significant issues.
– Algorithms to predict individual fault conditions.
– With advanced sensors, not only it is possible to forecast individual sensor data, but it is also possible to predict specific machine faults
– Multi-Application based Solution
For more information regarding eM PreA, download the pdf below.